Enables concurrent access to data in memory in a secure, multiuser environment. Data and analytical workload operations are distributed across nodes, in parallel, and are multithreaded on each node for very fast speed.

Drag-and-drop interface lets data engineers quickly build and run transformations, augment data and join data within the integrated visual pipeline of activities. All actions are performed in memory to maintain data structure consistency.

Integrated text analytics

Lets you explore all textual data, not just a subset, to gain new insights about unknown themes and connections.

Innovative statistical, data mining and machine learning techniques

Provides access to an incredibly broad set of modern statistical, machine learning, deep learning and text analytics algorithms in a single environment. Analytical capabilities include clustering, different flavors of regression, random forests, gradient boosting models, support vector machines, natural language processing, topic detection and more.

Model assessment and scoring

Test different modeling approaches in a single run and compare results of multiple supervised learning algorithms with standardized tests to quickly identify champion models. Then operationalize analytics in distributed and traditional environments with automatically generated SAS score code.

Accessible and cloud-ready

Modelers and data scientists can access SAS capabilities from their preferred coding environment, whether it's Python, R, Java or Lua. And with SAS Viya REST APIs, you can add the power of SAS to other applications.

From data management to model development and deployment, everyone works in the same, integrated environment.

Solve complex analytical problems faster.

SAS Visual Data Mining and Machine Learning, which runs on SAS® Viya®, combines data wrangling, exploration, feature engineering and modern statistical, data mining and machine learning techniques in a a single, scalable in-memory processing environment. The solution provides a very visual and highly collaborative workspace that supports a variety of users with different skill sets.

Empower users with language options.

Don't know SAS code? No problem. SAS Visual Data Mining and Machine Learning lets you embed open source code within an analysis, and call open source algorithms seamlessly within a Model Studio flow. This facilitates collaboration across your organization, because users can program in the language of their choice. The new node in Model Studio is agnostic to Python or R software versions; any version can be used as the code is passed.

Explore multiple approaches quickly to find the optimal solution.

Superior performance from massive parallel processing and the feature-rich building blocks for machine-learning pipelines let you explore and compare multiple approaches rapidly. You can quickly and easily find the optimal parameter settings for diverse machine learning algorithms – including decision trees, random forests, gradient boosting, neural networks, support vector machines and factorization machines – simply by selecting the option you want. Complex local search optimization routines work hard in the background to efficiently and effectively tune your models. The solution also lets you combine unstructured and structured data in integrated machine learning programs for more valuable insights from new data types. And reproducibility in every stage of the analytical life cycle delivers answers and insights you can trust.

Boost the productivity of your analytical teams.

Data scientists and other analytical professionals can get highly accurate results from a single, collaborative environment that supports the entire machine-learning pipeline. The solution enables a variety of users to access and prepare data. Perform exploratory analysis. Build and compare machine learning models. Create score code for implementing predictive models. Execute one-click model deployment. And you can do all this faster than ever before.

Reduce latency between data and decisions.

To enhance collaborative understanding, the solution provides all users with business-friendly annotations within each node describing what methods are being run, as well as information about the methods, results and interpretation. Standard interpretability reports are also available in all modeling nodes, including LIME, ICE, PD plots, etc.

Look Who's Working Smarter With SAS®

Get to Know SAS® Visual Data Mining and Machine Learning

This solution runs on SAS® Viya®, which has the breadth and depth to conquer any analytics challenge, from experimental to mission critical. SAS Viya extends the SAS Platform to enable everyone – data scientists, business analysts, developers and executives alike – to collaborate and realize innovative results faster.